Taking questions Now for Building a Baby Automated Trading system Event Tonight
I am taking questions for this event tonight at 7PM EDT. I got a bunch already. I cannot received them within a few hours of this time, I may not be able to answer your question!
Where to ask?
Email them or comment by asking them here on my Facebook Quantlabsnet page
Understanding your own coding is most predictable. I have many folks who lost thousands dues to bad programmers. This is what I have experienced among folks like yourself.
Here is what I will cover to build your ‘baby algo trading system’:
1. It depends on your asset class and broker of choice.
2. Sample way to download data with 3rd party solutions ranging from Excel to Java ion source source scanners.
3. How to use a Python package to do quick analysis using a popular technical analysis library
4. Analysis the results to assess trading order decisions
5. Which brokers with packages to execute orders
This will take place:
Note that this takes place TONIGHT!
You are invited to a Zoom webinar.
When: Sep 4, 2018 11:00 AM Eastern Time (US and Canada)
Topic: My WebinarWebinar event: Build a baby automated trading system with algos require streaming
Please click the link below to join the webinar:
https://zoom.us/j/309454798
Or iPhone one-tap :
US: +16465588656,,309454798# or +16699006833,,309454798#
Or Telephone:
Dial(for higher quality, dial a number based on your current location):
US: +1 646 558 8656 or +1 669 900 6833
Webinar ID: 309 454 798
International numbers available: https://zoom.us/u/xPHi0HZj
New course!! Building Python algo trading system with Bitcoin an crypto currency focus
More details will follow on how to get access with dates of the live bootcamp editions. Note that the total number of videos in between 3-4 hrs.
Remember this is the first draft of this:
COURSE NAME – Cryptocurrency and Algo Trading Infrastructure with Python: A Practical tutorial for Python developers
Sub-title – Discover the secrets behind trading infrastructure components, high speed in-memory NOSQL database options, cryptocurrency exchanges and simple technical indicators, and more. And use the same techniques in your Python code.
AUTHOR NAME – Bryan Downing
DURATION –
OVERVIEW – As Bitcoin ruled the financial news cycle in recent times, many have had a peak interest in cyrpto currency along with systematic trading. There are many advanced trading research techniques including machine learning, AI, or quant. This course was created for the ‘newbie’ who has a basic understand in popular programming languages but easy to learn such as Python. A focus of technical analysis was chosen since it is popular among retail traders. It is also seems to offer more predictable results as opposed to harder to learn concepts such as quant or machine learning. In essence, a simpler with more effective techniques were purposely chosen to get someone with basic programming knowledge (eg. Python) to get ramped up faster! It is very hopeful any student will become more confident in their capabilities to complete this without the unnecessary complexities that usually hold back their success.
TARGET AUDIENCE – Python programmers (including data scientists etc.) who want to understand algo techniques and apply them into a primitive automated trading system. Pro or Retail traders who have an interest in learning the basics of Python and systematic trading.
KEY FEATURES
Infrastructure modern component implementation fo an algo trading system
Basic coverage of crypto currency Python packages and crypto currency exchanges
Technical analysis library package use for strategy idea development
APPROACH –
Videos and sample Python source code scripts are made available at time of presentation. Note that scripts are meant to to be small and simple for easiest consumption. Advanced techniques are stripped out to ensure completion of this course. This can be used as a launching to pad to understand the components of a primitive algo trading system In short, it is devised in a way to get you up and running as quickly as possible.
WHAT WILL YOU LEARN
The major components in any trading system
Broker and asset class options
How crypto currency (e.g. Bitcoin) has becomes a hotbed of profit potential
Strategy coding basics to help in analyzing using popular techncial analysis techniques
All software mentioned is open and source with the exception of ChartDirector which is used for visualization.
ABOUT THE AUTHOR –
SUMMARY OF CONTENT
Why Python for my algos and automated trading? Which tools for development? Why Python over other programming languages?
Intro to NOSQL for highest performance in your systematic/algo/automated trading
Crypto Currency Exchange Overview and Python CCXT Package
Crypto Idea strategy generation using forward looking data as similar to financial institutions who analyze and trade popular alt coins including Bitcoin
Read exchange data with flat files
Pretty trading charts with ChartDirector
Using TA-Lib like package popular technical analysis for strategy development
COURSE ROADMAP
SECTION 1 – Programming Language Overview
SECTION DURATION – 28 minutes
SECTION DESCRIPTION – Covers pros and cons of each language you may come across on your journey with algo/automated trading. I also ist items you will need to consider when you want do live trading as well using correct concepts of High Frequency Trading (HFT) I cover 5 languages including:
R
Python
Java
C#/.NET
C and C++
MATLAB
SECTION 2 – Python tools and methodology
SECTION DURATION – 43 minutes
SECTION DESCRIPTION – Covers all elements of Python 2 vs 3 including a high level of ‘HelloWorld’ example. Also covers from a newbie’s POV on non essential Jypter and Machine Learning packages.
Python 2 vs 3
PIP the package manager
Python install options on operating systems
Tools like popular editors/IDEs e.g. Sublime
Simple Debugging techniques
Very high level concepts of popular machine learning frameworks and Juptyr use cases
SECTION 3 – Options to Capture Market Data
SECTION DURATION – 28 minute
SECTION DESCRIPTION –Different options for market data including free vs paid
IEX and IQFeed
LMAX and Interactive Brokers broker overview options
Dukascopy Forex.CFD broker Duka Python Package
Intro to JForex platform to create CSV using Java example
SECTION 4 – How to create Pandas dataframe to manipulate data
SECTION DURATION – 10 minutes
SECTION DESCRIPTION – Simple Python script that does the following
SECTION DESCRIPTION – As the original TA-LIB can be complicated to build yet along with the buggy TA-Lib Python package, there was another alternative that came up. A much simpler approach with the popular TA-LIB shows a simpler demo of running various indicators. These examples include:
Bollinger Band
Exponential Moving Average
Standard Deviation
Relative Strength Indicator
SECTION 6 – Redis NOSQL Overview and Sample
SECTION DURATION – 30 minutes
SECTION DESCRIPTION –NOSQL Database of choice
Why this is used
Open source and benchmarks
Compared against popular open source HFT project
Server and client edition
Python code demos
SECTION 7 – Funding Crypto Currency account
SECTION DURATION – 6 minute
SECTION DESCRIPTION –Options to cover to fund via bank credit card or use an anonymous credit card. Note that these option can be removed, invalid, or change without notification.
Different credit card option sources
Why banks block funding crypto currency via credit card
Round about way to fund anonymously via credit
SECTION 9 – Crypto Currency Outlook and CCXT Python Package overview
SECTION DURATION – 20 minute
SECTION DESCRIPTION –Over of Python package working examples with no registration needed for popular exchanges
Intro to CoinMarket.com to depend on volume
Reliable exchanges at time of recording
Advantages of Pyrhon option vs web programming languages
Examples of CCXT Python Package
SECTION 10 – Crypto Currency trading idea with forward looking data tips for your strategy idea
Crypto Currency trading idea with forward looking data for your strategy
SECTION DURATION – 11 minutes
SECTION DESCRIPTION –This is a set of ideas where you can use forward looking data to see how institutions gauge Bitcoin. These include:.
NVT Ratio
Futures and Options market
COT reports
Use of CoinMarketCap.com
SECTION 11– Intro to ChartDirector for Python
SECTION DURATION – 19 minutes
SECTION DESCRIPTION –This is an overall demo of features and how to install commercial ChartDirector for Python.
How to install on Mac or Linux/Unix like systems
Advantages over other open source Python packages like Matplotlib or Seaborn
Benefits of ChartDirector
Hints of Developing Interactive Self Standalone chart with potential live charting
Note that charts are generated via operating platform console terminal
This will vary on a product or Python package basiss. This example is relatively basic.
Minimum Hardware Requirements
For successful completion of this course, students will require computer systems with at least the following:
OS: Any
Processor: Minimal
Memory: 2 GB but may need 4+ GB if you to choose to install VirtualBox with Ubuntu Linux
Storage: Minimal
Recommended Hardware Requirements
For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:
OS: In order of preference of MacOS, Linux (e.g. Ubuntu), and Windows
Processor: Any
Memory: 2 GB but may need more 4 GB if you to choose install VirtualBox with Ubuntu Linux
Storage: 12 GB
Software Requirements
Operating system: See above
Browser: Any
Python 2.7 but prefer 3.x.
Sublime
Links and installation are provided in video module as required.
I was wondering if you figured out what you were going to do about your server(s) situation?
You talked about getting some kind of cloud solution, on top of a hardware server. I think you mentioned things like: redundancy and failover on linux Ubuntu.
You also said you probably would not be able to find things like this at Canada Computers…
So where would you go and what are the economics associated? Could this be done for under a $1000? What hardware and software options would be needed?
A colleague at work said I could buy a raid card to put into a computer with the proper software and cooling system so it could run 24/7 as a server.
What are your thoughts?
Ok. Fair enough.
I guess this is not a decision to be made over a short period of time. …lots to think about I guess.
I have worked in graphics departments that use a ton of data, so the first thing that came to mind was a raid server.
The only problem is that I don’t know if this is an option at and whether I need a very specific solution.
I made a video for all these answers
http://www.deltaserverstore.com/dell-server.html
After a week+ of watching videos and taking notes (I do a lot of in-depth documentation, btw), I have notes on about 8 videos on Python, but decided to take a break and watch some of the other video links you sent… it’s tough to keep up.
There was a seminar video, about 32 minutes with this European company who did a powerpoint on their algo trading system…. very informative.
They discussed how they use Python for their research, simulation and data engines/servers, etc. and did C++ coding for their low level code. ( 1 am only 10 minute into it).
Question:
What are you investing in, in terms of hardware, coding and other things for your system? and…
Do you have a template that I could follow to build my system? Could you help me with that?
I am gung ho about this and want to start doing something with it.
Also (I know I keep harping on this but it is pivotal you sign for this!)
I have also announced I will be moving this ‘newsletter’ to another server from Infusionsoft. You can also get my free 2 PDFs on (in case you never got them):
Trade Like a Boss
Tecbnical Secrets in Algo Trading
You can also be part of this new newsletter on this server. I am thinking of actually discontinuing this current one you are reading from. It has been highly recommended to manually opt in yourself into this new server.
How Cliff Asness Became A Billionaire Building a Vanguard ala hedge fund
He did by focusing on systematic trading models no different than Vanguard. Remember they are considered on of the largest HFT players on the planet
Started as a quantitative hedge fund firm, AQR stands for Applied Quantitative Research….Asness has moved away from hedge funds and aggressively into lower-fee, liquid and transparent products, including mutual funds, that use computer models, often to replicate hedge fund returns.
